Another approach for dense depth estimation is to start from depth sensors like LiDARs, and use depth completion to interpolate the missing depth values based on RGB data. Despite of impressive results achieved by recent methods such as [1]}, [2]}, [3]} they are mainly suitable for cases with relatively high 3D point density, but do not perform well with sparse point clouds.
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